Including indigenous knowledge in species distribution modeling for increased ecological insights

Area of Science:

• Ecological modeling
• Indigenous knowledge systems
• Conservation biology

Background:

• Indigenous knowledge offers valuable environmental insights but is underutilized in ecological modeling.
• Species distribution models (SDMs) are crucial for ecological research and conservation.
• Integrating diverse knowledge sources can enhance SDM accuracy and applicability.

Purpose of the Study:

• To develop a framework combining Indigenous knowledge and survey data for species distribution modeling.
• To model the distribution of the threatened greater bilby (Macrotis lagotis) using a collaborative approach.
• To assess the influence of Indigenous knowledge on SDM predictions and conservation insights.

Main Methods:

• A structured elicitation process was used to gather Martu (Aboriginal people of the Australian western deserts) occurrence knowledge.
• Species distribution models were created using the Maxent program with both Martu knowledge and track-based survey data.
• Statistical frameworks were employed to combine and analyze the two data types.

Main Results:

• Martu knowledge-based models predicted broader species distributions than survey data alone.
• Combined models indicated potential local declines in greater bilby populations, corroborated by Martu observations.
• Both data sources exhibited sampling bias, impacting model predictions and performance.

Conclusions:

• Intercultural approaches integrating Indigenous knowledge and scientific data enhance species distribution modeling.
• This integrated approach can improve the management of threatened and culturally significant species.
• Martu knowledge provided critical context on habitat associations, ecosystem dynamics, and disturbance regimes.